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O: Fachverband Oberflächenphysik

O 52: Nanostructures at Surfaces: Dots, Particles, Clusters

O 52.1: Poster

Dienstag, 21. März 2017, 18:30–20:30, P1C

A Neural Network Potential for the Simulation of Copper Clusters on Zinc Oxide — •Martín Leandro Paleico and Jörg Behler — Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, Germany

A catalyst composed of large copper and zinc oxide nanoparticles is utilized in the industrial synthesis of methanol. Studying this system requires a simulation method capable of handling thousands of atoms with ab-initio accuracy, but with computational efficiency comparable to classical force fields. For this purpose Neural Network Potentials (NNP) are trained using DFT reference data, to reproduce the potential energy surface of the system.

The current work focuses on the first results for the ternary copper-zinc oxide system. In particular, the growth of copper clusters on zinc oxide surfaces is studied through combined molecular dynamics and Monte Carlo simulations, utilizing a NNP to provide the energies and forces.